Imaging Coil Research Articles

A centralized frost detection and estimation scheme for Internet-connected domestic refrigerators

Frost accumulation on heat exchange units is a significant problem in refrigeration systems, adversely affecting their operating performance and thereby leading to increased power consumption. Therefore, timely detection and accurate quantification of frost are crucial for effective defrosting strategies. This study presents a novel centralized cloud-based IoT scheme for frost detection and thickness estimation. The image processing is performed on the cloud server to process evaporator coil images for frost thickness quantification. Experiments were conducted on a domestic refrigerator to assess the effectiveness of the proposed image-processing approach and determine latency and processing time. The presented scheme effectively quantifies frost thickness on the evaporator in the 1–5 mm range with a 10.8% error margin. The total inference time, which includes image acquisition, pre-processing, transmission latency, and frost thickness estimation, is approximately 5.15 seconds. The results demonstrate that the proposed image processing method performs comparably to conventional sensors and similar image processing techniques. Moreover, the centralized cloud-based IoT architecture presented effectively meets the scalability demands of consumer refrigerators.

Sodium MRI of the skin using a surface coil to investigate and reduce signal loss and bias.

The purpose was to improve sodium MRI of human skin using a surface coil and twisted projection imaging with smaller, reshaped voxels. Calf skin sodium images were acquired in 14 healthy adults using twisted projection imaging with short TE ˜ 0.1 ms, first with a volume coil and voxels (1.5 × 1.5 × 15 = 34 mm3) reflecting the widely adopted skin imaging protocol (VolPencil). A 5-cm-diameter surface coil then facilitated 5× smaller (0.8 × 0.8 × 10 = 6.4 mm3) voxels with similar signal to noise ratio (SNR) in the same 12-min scan time (SurfPencil). "Pencil-shaped" voxels were then replaced with "pancake-shaped" (0.4 × 4 × 4 = 6.4 mm3) voxels, matching the anatomy of pressed flat skin (SurfPancake). Surface coil B1 was investigated with the novel use of spin-3/2 simulation. Protocol modifications were tested for signal increase (reduced loss) and correlation with (bias by) skin thickness. Higher resolution SurfPencil yielded 44% ± 16% greater skin sodium image intensity than VolPencil, whereas SurfPancake yielded an additional 20% ± 9% (p < 1e-8), reflecting reduced signal loss. Over the 1.0 to 1.8 mm skin thickness across participants, sodium intensity significantly increased 56% ± 19% and 44% ± 12% for VolPencil and SurfPencil, respectively (p < 0.003), but not for SurfPancake, reflecting reduced bias. Imaging yielded skin sodium concentration of 34 ± 5 mM for SurfPancake. This is greater than the ˜20 mM measures from the widely adopted protocol, but simulation (matching experimental trends) identified a remaining 64% signal loss; compensation yields 95 ± 15 mM. Surface coil imaging and "pancake" voxel reshaping increased skin sodium intensity and reduced bias by skin thickness. Simulated loss compensation yields skin sodium concentration similar to that measured by atomic absorption spectroscopy.

A deep brain stimulation-conditioned RF coil for 3T MRI.

To develop and test an MRI coil assembly for imaging deep brain stimulation (DBS) at 3 T with a reduced level of local specific absorption rate of RF fields near the implant. A mechanical rotatable linearly polarized birdcage transmitter outfitted with a 32-channel receive array was constructed. The coil performance and image quality were systematically evaluated using bench-level measurements and imaging performance tests, including SNR maps, array element noise correlation, and acceleration capabilities. Electromagnetic simulations and phantom experiments were performed with clinically relevant DBS device configurations to evaluate the reduction of specific absorption rate and temperature near the implant compared with a circular polarized body coil setup. The linearly polarized birdcage coil features a block-shaped low electric field region to be co-aligned with the implanted DBS lead trajectory, while the close-fit receive array enables imaging with high SNR and enhanced encoding capabilities. The 3T coil assembly, consisting of a rotating linear birdcage and a 32-channel close-fit receive array, showed DBS-conditioned imaging technology with substantially reduced heat generation at the DBS implants.

Accelerated cardiac cine with spatio-coil regularized deep learning reconstruction.

To develop an iterative deep learning (DL) reconstruction with spatio-coil regularization and multichannel k-space data consistency for accelerated cine imaging. This study proposes a Spatio-Coil Regularized DL (SCR-DL) approach for iterative deep learning reconstruction incorporating multicoil information in data consistency and regularizer. SCR-DL uses shift-invariant convolutional kernels to interpolate missing k-space lines and reconstruct individual coil images, followed by a regularizer that operates simultaneously across spatial and coil dimensions using learned image priors. At 8-fold acceleration, SCR-DL was compared with Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA), sensitivity encoding (SENSE)-based DL and spatio-temporal regularized (STR)-DL reconstruction. In the retrospective undersampled cine, images were quantitatively evaluated using normalized mean square error (NMSE) and structural similarity index measure (SSIM). Additionally, agreement for left-ventricular ejection fraction and left-ventricular mass were assessed using prospectively accelerated cine images at 2-fold and 8-fold accelerations. The SCR-DL algorithm successfully reconstructed highly accelerated cine images. SCR-DL had significant improvements in NMSE (0.03 ± 0.02) and SSIM (91.4% ± 2.7%) compared with GRAPPA (NMSE: 0.09 ± 0.04, SSIM: 69.9% ± 11.1%; p < 0.001), SENSE-DL (NMSE: 0.07 ± 0.04, SSIM: 86.9% ± 3.2%; p < 0.001), and STR-DL (NMSE: 0.04 ± 0.03, SSIM: 90.0% ± 2.5%; p < 0.001) with retrospective undersampled cine. Despite the 3-fold reduction in scan time, there was no difference between left-ventricular ejection fraction (59.8 ± 4.5 vs. 60.8 ± 4.8, p = 0.46) or left-ventricular mass (73.6 ± 19.4 g vs. 73.2 ± 19.7 g, p = 0.95) between R = 2 and R = 8 prospectively accelerated cine images. SCR-DL enabled highly accelerated cardiac cine imaging, significantly reducing breath-hold time. Compared with GRAPPA or SENSE-DL, images reconstructed with SCR-DL showed superior NMSE and SSIM.

Research on FPC coils with limited turns in planar electromagnetic tomography

Electromagnetic tomography (EMT) is a non-destructive testing method that reconstructs electrical parameter distribution based on boundary electromagnetic measurement data along electromagnetic rotation projection. The coil is a critical component of the EMT system, used to excite and detect changing magnetic fields. The performance of excitation-detection with specific coils directly affects the quality of the reconstructed image. The traditional EMT coils are wound coils. The excitation-detection performance of the coils is enhanced by increasing the number of turns to obtain better imaging quality. A larger coil volume has better sensitivity, but it cannot meet the space constraints of many applications. To solve this problem, this paper proposes a method using extremely thin FPC coil arrays as EMT sensors. To verify the feasibility of FPC coil imaging with a limited number of turns, firstly, this article analyses the excitation-detection capabilities of FPC coil with 1 to 12 turns through a combination of simulation and experiment. Secondly, the impact of excitation-detection capability on the EMT sensitivity matrix was studied. Finally, a 4×4 8-Turns FPC coil sensor was designed for image reconstruction experiments. The experimental results show that FPC coils with limited turns can be used for image reconstruction and to solve the problem of planar nondestructive testing in a small space.

Challenges of Imaging the Greater Occipital Nerve Using Magnetic Resonance Imaging.

Migraine headaches are a significant global health concern, frequently managed with varying levels of success. Compression of the greater occipital nerve (GON) is hypothesized to contribute to pathology in some migraine patients, making extracranial nerve decompression surgery a potential intervention for refractory cases. However, accurate methods to image the GON along its tortuous course still need to be explored. Our group has developed magnetic resonance imaging sequences to track the GON. Yet, many challenges were met, which included navigating the GON's complex anatomy, understanding anatomical variants, and designing advanced magnetic resonance imaging sequences and coils to image the posterior scalp. Addressing these hurdles is vital to capture and understand GON pathology and guide potential interventions.

Linear Bloch-Siegert phase-encoded low-field MRI: RF coils, pulse sequence, and image reconstruction.

Conventional gradient systems have several weaknesses including high cost and bulk. As a step towards addressing these while providing new degrees of freedom for spatial encoding and system design in Magnetic Resonance Imaging (MRI), a radio frequency (RF) gradient encoding system and pulse sequence for phase encoding using the Bloch-Siegert (BS) shift were developed. Optimized BS spatial encoding coils with bucking windings (counter-wound loops) were designed and constructed, along with compatible homogeneous imaging coils for excitation and signal reception. Two coil systems were developed: one for phantom imaging and a second for human wrist imaging. BS phase-encoded imaging and BS RF pulse simulations were performed. Pulse sequences were designed for linear stepping in k-space and implemented on a 47.5-mT scanner to image resolution phantoms in both coil setups. Reconstructions were performed using both the full -based encoding fields for each BS pulse amplitude and using inverse discrete Fourier transforms. A gradient was used for frequency encoding during signal readout, and the third axis was projected. Specific absorption ratio (SAR) calculations were performed for the wrist coil to determine the safety of BS-based RF encoding for fields in the low field MRI regime. The optimized RF spatial encoding coils resulted in higher linearity ( and 0.9921 in the phantom and wrist coils, respectively) than coils used in previous work. The phantom and wrist imaging coils were validated in simulations and experimentally to produce a peak G and 0.8 G with 12-W input power, respectively, in the field-of-view (length = 11 cm) used for imaging. Nominal imaging resolutions of 5.22 and 7.21 mm were, respectively, achieved by the two-coil systems in the RF phase-encoded dimension. Coil systems, pulse sequences, and image reconstructions were developed for linear RF phase encoding using the BS shift and validated using a 47.5-mT open low field scanner, establishing a key component required for gradient-free imaging at low field strengths.

A 3D surface coil with deep learning‐based noise reduction for parotid gland imaging at 7T

AbstractBackgroundBackground: Parotid gland neoplasms occur near the facial nerve. Hence, it is crucial to determine whether the malignant neoplasms involve the facial nerve and whether sacrifice of the nerve in surgery is necessary. Furthermore, while 20% of all neoplasms are malignant, the most common benign neoplasm, pleomorphic adenoma, has a risk for malignant transformation, making early detection and treatment essential. 7T magnetic resonance imaging offers increased signal‐to‐noise ratio (SNR) and sensitivity.AimIn this work, we address imaging the parotid gland since it remains challenging at 7T because of its spatial location.Materials and MethodsHere, we present a novel three‐dimensional surface coil (3D Coil) architecture that offers increased depth penetration and SNR compared to the single channel surface coil. We further developed a deep learning (DL)‐based noise reduction method that receives inputs from three elements of the 3D Coil.ResultsThe 3D coil with DL‐based denoising method offers twice the SNR compared to the single channel surface coil for parotid gland imaging at 7T.Discussion and ConclusionThe proposed 3D Coil and DL‐based noise reduction method offers a promising way of achieving higher SNR for parotid salivary gland imaging at 7T, paving the road for clinical applications.

Endovaginal coil for pelvic high-resolution magnetic resonance imaging of cervical cancer: a preliminary parameter optimization study

Endovaginal coil for pelvic high-resolution magnetic resonance imaging of cervical cancer: a preliminary parameter optimization study

A Closed Formalism for Anatomy-Independent Projection and Optimization of Magnetic Stimulation Coils on Arbitrarily Shaped Surfaces.

Transcranial magnetic stimulation (TMS) is a popular method for the noninvasive stimulation of neurons in the brain. It has become a standard instrument in experimental brain research and has been approved for a range of diagnostic and therapeutic applications. These applications require appropriately shaped coils. Various applications have been established or approved for specific coil designs with their corresponding spatial electric field distributions. However, the specific coil implementation may no longer be appropriate from the perspective of available material and manufacturing opportunities or considering the latest understanding of how to achieve induced electric fields in the head most efficiently. Furthermore, in some cases, field measurements of coils with unknown winding or a user-defined field are available and require an actual implementation. Similar applications exist for magnetic resonance imaging coils. This work aims at introducing a complete formalism free from heuristics, iterative optimization, and ad-hoc or manual steps to form practical stimulation coils with individual turns to either equivalently match an existing coil or produce a given field. The target coil can reside on practically any sufficiently large or closed surface adjacent to or around the head. The method derives an equivalent field through vector projection exploiting the well-known Huygens' and Love's equivalence principle. In contrast to other coil design or optimization approaches recently presented, the procedure is an explicit forward Hilbert-space vector projection or basis change. For demonstration, we map a commercial figure-of-eight coil as one of the most widely used devices and a more intricate coil recently approved clinically for addiction treatment (H4) onto a bent surface close to the head for highest efficiency and lowest field energy. The resulting projections are within ≤4% of the target field and reduce the necessary pulse energy by more than 40%.

A birdcage transmit, 24-channel conformal receive array coil for sensitive 31P magnetic resonance spectroscopic imaging of the human brain at 7 T.

Phosphorus (31P) magnetic resonance spectroscopic imaging (MRSI) can serve as a critical tool for more direct quantification of brain energy metabolism, tissue pH, and cell membrane turnover. However, the low concentration of 31P metabolites in biological tissue may result in low signal-to-noise ratio (SNR) in 31P MRS images. In this work, we present an innovative design and construction of a 31P radiofrequency coil for whole-brain MRSI at 7 T. Our coil builds on current literature in ultra-high field 31P coil design and offers complete coverage of the brain, including the cerebellum and brainstem. The coil consists of an actively detunable volume transmit (Tx) resonator and a custom 24-channel receive (Rx) array. The volume Tx resonator is a 16-rung high-pass birdcage coil. The Rx coil consists of a 24-element phased array composed of catered loop shapes and sizes built onto a custom, close-fitting, head-shaped housing. The Rx array was designed to provide complete coverage of the head, while minimizing mutual coupling. The Rx configuration had a mean reflection coefficient better than -20 decibels (dB) when the coil was loaded with a human head. The mean mutual coupling ( ) among Rx elements, when loaded with a human head, was -16 dB. In phantom imaging, the phased array produced a central SNR that was 4.4-fold higher than the corresponding central SNR when operating the 31P birdcage as a transceiver. The peripheral SNR was 12-fold higher when applying the optimized phased array. In vivo 3D 31P MRSI experiments produced high-quality spectra in the cerebrum gray and white matter, as well as in the cerebellum. Characteristic phosphorus metabolites related to adenosine triphosphate metabolism and cell membrane turnover were distinguishable across all brain regions. In summary, our results demonstrate the potential of our novel coil for accurate, whole-brain 31P metabolite quantification.

A visual defrosting control method for air source heat pump system based on machine vision

Frosting on the coil of the air source heat pump (ASHP) significantly affects its performance. An accurate defrosting control method is essential for the ASHP unit. Here, a novel visual defrosting control method based on machine vision is proposed. The frosting degree of the unit is accurately obtained by frosting image analysis with digital image processing to achieve on-demand defrosting. Fractal dimension, frosting degree coefficient, and single-circuit frosting evenness value are introduced to evaluate the frosting degree of coil images. The image acquisition point is determined with confusion matrix. Based on this, the logical framework of the proposed method is constructed, in which the defrosting starting and termination conditions are set as the moment when the frosting degree coefficient is equal to 0.9 and 0, respectively. A multi-variable model of fractal dimension is fitted, which improves the generalization of the proposed method. Finally, comparative experiments are conducted between the proposed method and the traditional temperature-time (T-T) method in typical cases. The results indicate that the COP and total heating capacity increase by 11.8 %, 10.6 % and 7.4 %, 6.6 %, respectively, and the defrosting frequency is reduced by 75 %, which demonstrates dominant advantages of the proposed method in accuracy, energy-saving, and indoor thermal comfort management.

An essentially radiation-transparent body coil integrated with a patient rotation system for MR-guided particle therapy.

The pursuit of adaptive radiotherapy using MR imaging for better precision in patient positioning puts stringent demands on the hardware components of the MR scanner. Particularly in particle therapy, the dose distribution and thus the efficacy of the treatment is susceptible to beam attenuation from interfering materials in the irradiation path. This severely limits the usefulness of conventional imaging coils, which contain highly attenuating parts such as capacitors and preamplifiers in an unknown position, and requires development of a dedicated radiofrequency (RF) coil with close consideration of the materials and components used. In MR-guided radiation therapy in the human torso, imaging coils with a large FOV and homogeneous B1 field distribution are required for reliable tissue classification. In this work, an imaging coil for MR-guided particle therapy was developed with minimal ion attenuation while maintaining flexibility in treatment. A birdcage coil consisting of nearly radiation-transparent materials was designed and constructed for a closed-bore 1.5 T MR system. Additionally, the coil was mounted on a rotatable patient capsule for flexible positioning of the patient relative to the beam. The ion attenuation of the RF coil was investigated in theory and via measurements of the Bragg peak position. To characterize the imaging quality of the RF coil, transmit and receive field distributions were simulated and measured inside a homogeneous tissue-simulating phantom for various rotation angles of the patient capsule ranging from 0° to 345° in steps of 15°. Furthermore, simulations with a heterogeneous human voxel model were performed to better estimate the effect of real patient loading, and the RF coil was compared to the internal body coil in terms of SNR for a full rotation of the patient capsule. The RF coil (total water equivalent thickness (WET) ≈ 420µm, WET of conductor ≈ 210µm) can be considered to be radiation-transparent, and a measured transmit power efficiency (B1 +/ ) between 0.17 µT/ and 0.26 µT/ could be achieved in a volume (Δz=216mm, complete x and y range) for the 24 investigated rotation angles of the patient capsule. Furthermore, homogeneous transmit and receive field distributions were measured and simulated in the transverse, coronal and sagittal planes in a homogeneous phantom and a human voxel model. In addition, the SNR of the radiation-transparent RF coil varied between 103 and 150, in the volume (Δz=216mm) of a homogeneous phantom and surpasses the SNR of the internal body coil for all rotation angles of the patient capsule. A radiation-transparent RF coil was developed and built that enables flexible patient to beam positioning via full rotation capability of the RF coil and patient relative to the beam, with results providing promising potential for adaptive MR-guided particle therapy.

Exploring Structural Sparsity of Coil Images from 3-Dimensional Directional Tight Framelets for SENSE Reconstruction

Exploring Structural Sparsity of Coil Images from 3-Dimensional Directional Tight Framelets for SENSE Reconstruction

IMJENSE: Scan-Specific Implicit Representation for Joint Coil Sensitivity and Image Estimation in Parallel MRI.

Parallel imaging is a commonly used technique to accelerate magnetic resonance imaging (MRI) data acquisition. Mathematically, parallel MRI reconstruction can be formulated as an inverse problem relating the sparsely sampled k-space measurements to the desired MRI image. Despite the success of many existing reconstruction algorithms, it remains a challenge to reliably reconstruct a high-quality image from highly reduced k-space measurements. Recently, implicit neural representation has emerged as a powerful paradigm to exploit the internal information and the physics of partially acquired data to generate the desired object. In this study, we introduced IMJENSE, a scan-specific implicit neural representation-based method for improving parallel MRI reconstruction. Specifically, the underlying MRI image and coil sensitivities were modeled as continuous functions of spatial coordinates, parameterized by neural networks and polynomials, respectively. The weights in the networks and coefficients in the polynomials were simultaneously learned directly from sparsely acquired k-space measurements, without fully sampled ground truth data for training. Benefiting from the powerful continuous representation and joint estimation of the MRI image and coil sensitivities, IMJENSE outperforms conventional image or k-space domain reconstruction algorithms. With extremely limited calibration data, IMJENSE is more stable than supervised calibrationless and calibration-based deep-learning methods. Results show that IMJENSE robustly reconstructs the images acquired at 5× and 6× accelerations with only 4 or 8 calibration lines in 2D Cartesian acquisitions, corresponding to 22.0% and 19.5% undersampling rates. The high-quality results and scanning specificity make the proposed method hold the potential for further accelerating the data acquisition of parallel MRI.

Any-nucleus distributed active programmable transmit coil.

There are 118 known elements. Nearly all of them have NMR active isotopes and at least 39 different nuclei have biological relevance. Despite this, most of today's MRI is based on only one nucleus-1H. To facilitate imaging all potential nuclei, we present a single transmit coil able to excite arbitrary nuclei in human-scale MRI. We present a completely new type of RF coil, the Any-nucleus Distributed Active Programmable Transmit Coil (ADAPT Coil), with fast switches integrated into the structure of the coil to allow it to operate at any relevant frequency. This coil eliminates the need for the expensive traditional RF amplifier by directly converting direct current (DC) power into RF magnetic fields with frequencies chosen by digital control signals sent to the switches. Semiconductor switch imperfections are overcome by segmenting the coil. Circuit simulations demonstrated the effectiveness of the ADAPT Coil approach, and a 9 cm diameter surface ADAPT Coil was implemented. Using the ADAPT Coil, 1H, 23Na, 2H, and 13C phantom images were acquired, and 1H and 23Na ex vivo images were acquired. To excite different nuclei, only digital control signals were changed, which can be programmed in real time. The ADAPT Coil presents a low-cost, scalable, and efficient method for exciting arbitrary nuclei in human-scale MRI. This coil concept provides further opportunities for scaling, programmability, lowering coil costs, lowering dead-time, streamlining multinuclear MRI workflows, and enabling the study of dozens of biologically relevant nuclei.

Unsupervised motion artifact correction of turbo spin-echo MRI using deep image prior.

In MRI, motion artifacts can significantly degrade image quality. Motion artifact correction methods using deep neural networks usually required extensive training on large datasets, making them time-consuming and resource-intensive. In this paper, an unsupervised deep learning-based motion artifact correction method for turbo-spin echo MRI is proposed using the deep image prior framework. The proposed approach takes advantage of the high impedance to motion artifacts offered by the neural network parameterization to remove motion artifacts in MR images. The framework consists of parameterization of MR image, automatic spatial transformation, and motion simulation model. The proposed method synthesizes motion-corrupted images from the motion-corrected images generated by the convolutional neural network, where an optimization process minimizes the objective function between the synthesized images and the acquired images. In the simulation study of 280 slices from 14 subjects, the proposed method showed a significant increase in the averaged structural similarity index measure by 0.2737 in individual coil images and by 0.4550 in the root-sum-of-square images. In addition, the ablation study demonstrated the effectiveness of each proposed component in correcting motion artifacts compared to the corrected images produced by the baseline method. The experiments on real motion dataset has shown its clinical potential. The proposed method exhibited significant quantitative and qualitative improvements in correcting rigid and in-plane motion artifacts in MR images acquired using turbo spin-echo sequence.

Design of miniatured MRI coils for MRI‐guided tumor diagnosis and hyperthermia therapy

AbstractIn this paper, the researchers offer a miniatured design of microstrip lines based on magnetic resonance imaging (MRI) coils that can be utilized to detect tumor tissues and to restore those tissues after radiotherapy. A 61.67% reduction in size was achieved in the MRI array dimensions when compared to the previously reported MRI coils. The reliability of the design specifications was verified. The proposed MRI coils could contribute two resonant modes. Primarily, these MRI coils were suitable for homogenous magnetic field and they enable radio frequency (RF) heating by generating a concentrated electric field |E|. The collective temperature and specific absorption ratio (SAR) have been estimated at Larmor frequency. In this study, it was possible to create a uniform magnetic flux density |B1| field operating at 500 MHz. These proposed coils were excited at 8.06 GHz. When simulating cancer in a biological system, healthy tissues were introduced into a Class A scenario and malignant tissues were introduced into a Class B scenario. According to these two scenarios, tumor tissues were magnetically (|B1|) homogeneous with a 44.1% standard deviation with rapidly raised temperature at 4.77°C. These MRI coils delivered an impact on diagnostic imaging and parallelly restored the cancerous tissues by hyperthermia.

Experimental observation of micro-tearing modes in the tokamak pedestal

A micro-tearing mode has been observed in electron temperature fluctuations and magnetic fluctuations with the frequency range of 80–120 kHz in the pedestal of the Experimental Advanced Superconducting Tokamak (EAST) using Electron Cyclotron Emission Imaging (ECEI) and Mirnov magnetic coil measurement. It appears in the type-I ELMs period after the L-H transition. The measured poloidal phase velocity of the electron temperature fluctuations is ∼40 km/s (f = 80–120 kHz) in the electron diamagnetic direction in the laboratory frame with the poloidal wave number around kΘ ∼0.15 /cm. The two-dimensional structure of MTMs is directly observed using two-dimensional Electron cyclotron emission imaging. The experiment confirmed that the electron temperature (ECEI) and radial electric field (Backward Doppler reflectometer) during MTM meet the pressure balance equation. Until now, the theory and simulation results showed that transport is in heat flux, small particle flux, while the experimental results of this paper indicate that the particle flux is small.

Troubleshooting and Quality Assurance in Hyperpolarized Xenon Magnetic Resonance Imaging: Tools for High-Quality Image Acquisition.

Hyperpolarized (HP) xenon magnetic resonance imaging (129Xe MRI) is a recently federal drug administration (FDA)-approved imaging modality that produces high-resolution images of an inhaled breath of xenon gas for investigation of lung function. However, implementing 129Xe MRI is uniquely challenging as it requires specialized hardware and equipment for hyperpolarization, procurement of xenon imaging coils and coil software, development and compilation of multinuclear MR imaging sequences, and reconstruction/analysis of acquired data. Without proper expertise, these tasks can be daunting, and failure to acquire high-quality images can befrustrating, and expensive. Here, we present some quality control (QC) protocols, troubleshooting practices, and helpful tools for129Xe MRI sites, which may aid in the acquisition of optimized, high-quality data and accurate results. The discussion will begin with an overview of the process for implementing HP 129Xe MRI, including requirements for a hyperpolarizer lab, the combination of 129Xe MRI coil hardware/software, data acquisition and sequence considerations, data structures, k-space and image properties, and measured signal and noise characteristics. Within each of these necessary steps lies opportunities for errors, challenges, and unfavorable occurrences leading to poor image quality or failed imaging, and this presentation aims to address some of the more commonly encountered issues. In particular, identification and characterization of anomalous noise patterns in acquired data are necessary to avoid image artifacts and low-quality images; examples will be given, and mitigation strategies will be discussed. We aim to make the 129Xe MRI implementation process easier for new sites while providing some guidelines and strategies for real-time troubleshooting.